Medizinische Universität Graz - Research portal
Selected Publication:
SHR Neuro Cancer Cardio Lipid Metab Microb
Oberbach, A; Bluher, M; Wirth, H; Till, H; Kovacs, P; Kullnick, Y; Schlichting, N; Tomm, JM; Rolle-Kampczyk, U; Murugaiyan, J; Binder, H; Dietrich, A; von Bergen, M; .
Combined Proteomic and Metabolomic Profiling of Serum Reveals Association of the Complement System with Obesity and Identifies Novel Markers of Body Fat Mass Changes.
J PROTEOME RES. 2011; 10(10): 4769-4788.
Doi: 10.1021/pr2005555
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- Co-authors Med Uni Graz
- Till Holger
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- Abstract:
- Obesity is associated with multiple adverse health effects and a high risk of developing metabolic and cardiovascular diseases. Therefore, there is a great need to identify circulating parameters that link changes in body fat mass with obesity. This study combines proteomic and metabolomic approaches to identify circulating molecules that discriminate healthy lean from healthy obese individuals in an exploratory study design. To correct for variations in physical activity, study participants performed a one hour exercise bout to exhaustion. Subsequently, circulating factors differing between lean and obese individuals, independent of physical activity, were identified. The DIGE approach yielded 126 differentially abundant spots representing 39 unique proteins. Differential abundance of proteins was confirmed by ELISA for antithrombin-III, clusterin, complement C3 and complement C3b, pigment epithelium-derived factor (PEDF), retinol binding protein 4 (RBP4), serum amyloid P (SAP), and vitamin-D binding protein (VDBP). Targeted serum metabolomics of 163 metabolites identified 12 metabolites significantly related to obesity. Among those, glycine (GLY), glutamine (GLN), and glycero-phosphatidylcholine 42:0 (PCaa 42:0) serum concentrations were higher, whereas PCaa 32:0, PCaa 32:1, and PCaa 40:5 were decreased in obese compared to lean individuals. The integrated bioinformatic evaluation of proteome and metabolome data yielded an improved group separation score of 2.65 in contrast to 2.02 and 2.16 for the single-type use of proteomic or metabolomics data, respectively. The identified circulating parameters were further investigated in an extended set of 30 volunteers and in the context of two intervention studies. Those included 14 obese patients who had undergone sleeve gastrectomy and 12 patients on a hypocaloric diet. For determining the long-term adaptation process the samples were taken six months after the treatment. In multivariate regression analyses, SAP, CLU, RBP4, PEDF, GLN, and C18:2 showed the strongest correlation to changes in body fat mass. The combined serum proteomic and metabolomic profiling reveals a link between the complement system and obesity and identifies both novel (C3b, CLU, VDBP, and all metabolites) and confirms previously discovered markers (PEDF, RBP4, C3, ATIII, and SAP) of body fat mass changes.
- Find related publications in this database (using NLM MeSH Indexing)
- Adipose Tissue - metabolism
- Adult -
- Bariatric Surgery - methods
- Biological Markers - blood
- Complement System Proteins - metabolism
- Computational Biology - methods
- Cross-Sectional Studies -
- Electrophoresis, Gel, Two-Dimensional - methods
- Enzyme-Linked Immunosorbent Assay - methods
- Humans -
- Image Processing, Computer-Assisted -
- Isoelectric Focusing - methods
- Life Style -
- Male -
- Mass Spectrometry - methods
- Metabolomics - methods
- Obesity - blood
- Find related publications in this database (Keywords)
- Proteomics
- Metabolomics
- obesity
- bariatric surgery
- weight loss therapy
- lifestyle intervention